A coordinated decomposition method for power traded in cascade hydropower stations in response to multi-scaled loads
Runoff and load uncertainty exacerbate the difficulty of scheduling and operation of multi-receiver-end giant hydropower plant clusters in Southwest China,which greatly affects the performance of hydropower plants'medium-and long-term traded power.In this paper,a power trading coordination method is proposed for multi-receiver-terminal and multi-scale differential loads of the cascade hydropower plants,and a runoff scenario gener-ation method based on Latin hypercubic sampling and K-means clustering is constructed considering the long-term runoff prediction error.By introducing load characteristic indexes,a typical load feature extraction method based on nonparametric estimation is proposed to accurately characterize the differential loads of the power grids of differ-ent receiver terminals.Meanwhile,in order to avoid the unbalanced influence on power allocation and curve de-composition,the load curve is reconstructed by using the peak-to-valley difference rate and the proportion of power delivery,and a multi-objective model is constructed to maximize the expected revenue from the peaking at the receiving end of the grid,and the planned power performance of the terraced hydropower plants.A validation analysis is carried out on the example of the actual project of sending power to seven provinces(municipalities)from four giant terrace hydropower stations in the main stream of a mega-basin in Southwest China.The results show that the proposed method can realize the reasonable distribution of annual planned power in the flood and dry periods and among provinces.At the same time,it is found that the interplay between the grid peak demand and the power station's power generation revenue is conducive to the coordination of the hydropower consumption program.
万方数据
维普
